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Title: A REAL TIME COAL CONTENT ORE GRADE (C2OG) SENSOR

This fifth quarterly technical report discusses the progress made on a machine vision technique for determining coal content and ore grades. Recent work has been devoted to implementing new hardware and examining defects in titanium sponge, a new application for the machine vision system. With the improvements in hardware and software, the data collection is much improved. Early results from data taken on titanium sponge defects indicate that some defects will be relatively easy to identify, but others will be much more difficult. Consequently, additional work is required with software algorithms for target recognition. Ongoing work will be divided into several fronts, which include data collection and analysis, improving the target recognition capabilities, and improving the electronic interface.
Authors:
Publication Date:
OSTI Identifier:
804933
Report Number(s):
FC26-01NT41057--05
TRN: US200223%%426
DOE Contract Number:
FC26-01NT41057
Resource Type:
Technical Report
Resource Relation:
Other Information: PBD: 24 Oct 2002
Research Org:
National Energy Technology Lab., Pittsburgh, PA (US); National Energy Technology Lab., Morgantown, WV (US)
Sponsoring Org:
US Department of Energy (US)
Country of Publication:
United States
Language:
English
Subject:
01 COAL, LIGNITE, AND PEAT; ALGORITHMS; COAL; DEFECTS; TARGETS; TITANIUM